Awesome MATLAB for Students

repository·main·Indexed 20 days ago

https://github.com/mathworks/awesome-matlab-students

A curated collection of resources for students using MATLAB and Simulink. Includes learning paths, interactive Onramps, cheat sheets for basic functions and visualization, guidance on hardware connectivity (Arduino, Raspberry Pi), and information on AI tools like MATLAB Copilot and AI Chat Playground.

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What's inside awesome-matlab-students

  1. Explore Industry and Academic Resources

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    MATLAB and Simulink provide specialized resources tailored to specific industries and academic disciplines.

    Industry & Application Areas

    Resources are available for:

    • Aerospace & Defense
    • Utilities & Energy
    • Automotive
    • Robotics
    • Industrial Automation
    • Communications
    • Medical Devices
    • Biotech and Pharma
    • Finance
    • Semiconductors
    • Electronics
    • Artificial Intelligence

    Academic Disciplines

    Resources are available for:

    • Physics
    • Chemistry
    • Mathematics
    • Neuroscience
    • Mechanical Engineering
    • Biological Sciences
    • Electrical Engineering
    • Chemical Engineering
    • Geoscience
  2. Explore Generative and Agentic AI with MATLAB

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    MathWorks provides several tools for integrating AI into your MATLAB and Simulink workflows:

    • MATLAB Copilot: Provides AI-powered assistance directly within the MATLAB desktop environment.
    • MATLAB AI Chat Playground: A free tool (with a MathWorks account) to experiment with AI, answer questions, and draft MATLAB code.
    • Generative AI Tools: A broader ecosystem including agentic toolkits and MCP (Model Context Protocol) integrations.
  3. Connect AI agents to MATLAB via Agentic AI Toolkits

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    You can connect AI coding agents (such as Claude Code, GitHub Copilot, Cursor, Gemini CLI, and Amp) to MATLAB and Simulink using the Model Context Protocol (MCP).

    Core Components

    • MATLAB MCP Core Server: The foundation that standardizes connections between AI agents and MATLAB for code execution, debugging, and automation.
    • MATLAB Agentic Toolkit: Provides curated expert skills for testing, debugging, app building, and code review.
      • Requirements: MATLAB R2020b or later and the MATLAB MCP Core Server.
    • Simulink Agentic Toolkit: Extends agentic AI to Simulink with 6 MCP tools (reading, editing, querying, testing models) and 7 agent skills.
      • Requirements: MATLAB R2023a or later with Simulink and the MATLAB MCP Core Server.
    • AI Coding Agent Prompts for MATLAB: A library of curated prompts to improve results when using agents like GitHub Copilot or Cursor.
  4. Use MathWorks Copilot products

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    MathWorks offers AI assistants built directly into the MATLAB and Simulink desktop environments. Note: These require a Copilot license.

    • MATLAB Copilot: An AI-powered assistant for MATLAB desktop and MATLAB Online to help with learning techniques and improving productivity.
    • Simulink Copilot: An AI-powered assistant for Simulink and Model-Based Design. It helps explain models/errors, guides design, and automates tasks like standards checking, testing, and code generation.
  5. Access General MATLAB and Simulink Resources

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    MathWorks provides several categories of resources for students to support their learning across different disciplines and applications:

    • Academic & Industry Specific Resources: Access solutions tailored to specific disciplines and industries.
    • Application Specific Support: Get help with specific MATLAB applications.
    • External Language Interfaces: Learn how to interface MATLAB with other programming languages.
    • Learning Media:
    • Interactive Examples: Find discipline-specific examples via MATLAB Central File Exchange.
  6. Practice MATLAB with interactive examples and Cody

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    You can improve your MATLAB skills through two primary methods:

    1. Interactive Modules: These include theoretical background, illustrations, and exercises. Examples include:

      • Treasure Hunt: A coding quest.
      • Machine Learning Methods: Clustering: Hands-on clustering fundamentals.
      • Fundamentals of Programming: Building a programming foundation.
      • Programming a Starter Project Using MATLAB and Python: Learning integration between MATLAB and Python.
    2. MATLAB Cody™: An interactive coding challenge platform on MATLAB Central. It provides short, automatically-graded problems to improve fluency and learn idiomatic solutions.

    Recommended Cody problem groups for beginners:

    • Introduction to MATLAB
    • MATLAB Onramp Practice
    • Basics on Vectors
    https://www.mathworks.com/matlabcentral/cody/